This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

Displaying 1 - 10 of 82
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Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups

Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different control algorithms. The focus

The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different control algorithms. The focus of this thesis is to design scheduling and power control algorithms in wireless networks, and analyze their performances. In this thesis, we first study the multicast capacity of wireless ad hoc networks. Gupta and Kumar studied the scaling law of the unicast capacity of wireless ad hoc networks. They derived the order of the unicast throughput, as the number of nodes in the network goes to infinity. In our work, we characterize the scaling of the multicast capacity of large-scale MANETs under a delay constraint D. We first derive an upper bound on the multicast throughput, and then propose a lower bound on the multicast capacity by proposing a joint coding-scheduling algorithm that achieves a throughput within logarithmic factor of the upper bound. We then study the power control problem in ad-hoc wireless networks. We propose a distributed power control algorithm based on the Gibbs sampler, and prove that the algorithm is throughput optimal. Finally, we consider the scheduling algorithm in collocated wireless networks with flow-level dynamics. Specifically, we study the delay performance of workload-based scheduling algorithm with SRPT as a tie-breaking rule. We demonstrate the superior flow-level delay performance of the proposed algorithm using simulations.
ContributorsZhou, Shan (Author) / Ying, Lei (Thesis advisor) / Zhang, Yanchao (Committee member) / Zhang, Junshan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The rapid advances in wireless communications and networking have given rise to a number of emerging heterogeneous wireless and mobile networks along with novel networking paradigms, including wireless sensor networks, mobile crowdsourcing, and mobile social networking. While offering promising solutions to a wide range of new applications, their widespread adoption

The rapid advances in wireless communications and networking have given rise to a number of emerging heterogeneous wireless and mobile networks along with novel networking paradigms, including wireless sensor networks, mobile crowdsourcing, and mobile social networking. While offering promising solutions to a wide range of new applications, their widespread adoption and large-scale deployment are often hindered by people's concerns about the security, user privacy, or both. In this dissertation, we aim to address a number of challenging security and privacy issues in heterogeneous wireless and mobile networks in an attempt to foster their widespread adoption. Our contributions are mainly fivefold. First, we introduce a novel secure and loss-resilient code dissemination scheme for wireless sensor networks deployed in hostile and harsh environments. Second, we devise a novel scheme to enable mobile users to detect any inauthentic or unsound location-based top-k query result returned by an untrusted location-based service providers. Third, we develop a novel verifiable privacy-preserving aggregation scheme for people-centric mobile sensing systems. Fourth, we present a suite of privacy-preserving profile matching protocols for proximity-based mobile social networking, which can support a wide range of matching metrics with different privacy levels. Last, we present a secure combination scheme for crowdsourcing-based cooperative spectrum sensing systems that can enable robust primary user detection even when malicious cognitive radio users constitute the majority.
ContributorsZhang, Rui (Author) / Zhang, Yanchao (Thesis advisor) / Duman, Tolga Mete (Committee member) / Xue, Guoliang (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Integrated photonics requires high gain optical materials in the telecom wavelength range for optical amplifiers and coherent light sources. Erbium (Er) containing materials are ideal candidates due to the 1.5 μm emission from Er3+ ions. However, the Er density in typical Er-doped materials is less than 1 x 1020 cm-3,

Integrated photonics requires high gain optical materials in the telecom wavelength range for optical amplifiers and coherent light sources. Erbium (Er) containing materials are ideal candidates due to the 1.5 μm emission from Er3+ ions. However, the Er density in typical Er-doped materials is less than 1 x 1020 cm-3, thus limiting the maximum optical gain to a few dB/cm, too small to be useful for integrated photonics applications. Er compounds could potentially solve this problem since they contain much higher Er density. So far the existing Er compounds suffer from short lifetime and strong upconversion effects, mainly due to poor quality of crystals produced by various methods of thin film growth and deposition. This dissertation explores a new Er compound: erbium chloride silicate (ECS, Er3(SiO4)2Cl ) in the nanowire form, which facilitates the growth of high quality single crystals. Growth methods for such single crystal ECS nanowires have been established. Various structural and optical characterizations have been carried out. The high crystal quality of ECS material leads to a long lifetime of the first excited state of Er3+ ions up to 1 ms at Er density higher than 1022 cm-3. This Er lifetime-density product was found to be the largest among all Er containing materials. A unique integrating sphere method was developed to measure the absorption cross section of ECS nanowires from 440 to 1580 nm. Pump-probe experiments demonstrated a 644 dB/cm signal enhancement from a single ECS wire. It was estimated that such large signal enhancement can overcome the absorption to result in a net material gain, but not sufficient to compensate waveguide propagation loss. In order to suppress the upconversion process in ECS, Ytterbium (Yb) and Yttrium (Y) ions are introduced as substituent ions of Er in the ECS crystal structure to reduce Er density. While the addition of Yb ions only partially succeeded, erbium yttrium chloride silicate (EYCS) with controllable Er density was synthesized successfully. EYCS with 30 at. % Er was found to be the best. It shows the strongest PL emission at 1.5 μm, and thus can be potentially used as a high gain material.
ContributorsYin, Leijun (Author) / Ning, Cun-Zheng (Thesis advisor) / Chamberlin, Ralph (Committee member) / Yu, Hongbin (Committee member) / Menéndez, Jose (Committee member) / Ponce, Fernando (Committee member) / Arizona State University (Publisher)
Created2013
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Description
A principal goal of this dissertation is to study stochastic optimization and real-time scheduling in cyber-physical systems (CPSs) ranging from real-time wireless systems to energy systems to distributed control systems. Under this common theme, this dissertation can be broadly organized into three parts based on the system environments. The first

A principal goal of this dissertation is to study stochastic optimization and real-time scheduling in cyber-physical systems (CPSs) ranging from real-time wireless systems to energy systems to distributed control systems. Under this common theme, this dissertation can be broadly organized into three parts based on the system environments. The first part investigates stochastic optimization in real-time wireless systems, with the focus on the deadline-aware scheduling for real-time traffic. The optimal solution to such scheduling problems requires to explicitly taking into account the coupling in the deadline-aware transmissions and stochastic characteristics of the traffic, which involves a dynamic program that is traditionally known to be intractable or computationally expensive to implement. First, real-time scheduling with adaptive network coding over memoryless channels is studied, and a polynomial-time complexity algorithm is developed to characterize the optimal real-time scheduling. Then, real-time scheduling over Markovian channels is investigated, where channel conditions are time-varying and online channel learning is necessary, and the optimal scheduling policies in different traffic regimes are studied. The second part focuses on the stochastic optimization and real-time scheduling involved in energy systems. First, risk-aware scheduling and dispatch for plug-in electric vehicles (EVs) are studied, aiming to jointly optimize the EV charging cost and the risk of the load mismatch between the forecasted and the actual EV loads, due to the random driving activities of EVs. Then, the integration of wind generation at high penetration levels into bulk power grids is considered. Joint optimization of economic dispatch and interruptible load management is investigated using short-term wind farm generation forecast. The third part studies stochastic optimization in distributed control systems under different network environments. First, distributed spectrum access in cognitive radio networks is investigated by using pricing approach, where primary users (PUs) sell the temporarily unused spectrum and secondary users compete via random access for such spectrum opportunities. The optimal pricing strategy for PUs and the corresponding distributed implementation of spectrum access control are developed to maximize the PU's revenue. Then, a systematic study of the nonconvex utility-based power control problem is presented under the physical interference model in ad-hoc networks. Distributed power control schemes are devised to maximize the system utility, by leveraging the extended duality theory and simulated annealing.
ContributorsYang, Lei (Author) / Zhang, Junshan (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Xue, Guoliang (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Communication networks, both wired and wireless, are expected to have a certain level of fault-tolerance capability.These networks are also expected to ensure a graceful degradation in performance when some of the network components fail. Traditional studies on fault tolerance in communication networks, for the most part, make no assumptions regarding

Communication networks, both wired and wireless, are expected to have a certain level of fault-tolerance capability.These networks are also expected to ensure a graceful degradation in performance when some of the network components fail. Traditional studies on fault tolerance in communication networks, for the most part, make no assumptions regarding the location of node/link faults, i.e., the faulty nodes and links may be close to each other or far from each other. However, in many real life scenarios, there exists a strong spatial correlation among the faulty nodes and links. Such failures are often encountered in disaster situations, e.g., natural calamities or enemy attacks. In presence of such region-based faults, many of traditional network analysis and fault-tolerant metrics, that are valid under non-spatially correlated faults, are no longer applicable. To this effect, the main thrust of this research is design and analysis of robust networks in presence of such region-based faults. One important finding of this research is that if some prior knowledge is available on the maximum size of the region that might be affected due to a region-based fault, this piece of knowledge can be effectively utilized for resource efficient design of networks. It has been shown in this dissertation that in some scenarios, effective utilization of this knowledge may result in substantial saving is transmission power in wireless networks. In this dissertation, the impact of region-based faults on the connectivity of wireless networks has been studied and a new metric, region-based connectivity, is proposed to measure the fault-tolerance capability of a network. In addition, novel metrics, such as the region-based component decomposition number(RBCDN) and region-based largest component size(RBLCS) have been proposed to capture the network state, when a region-based fault disconnects the network. Finally, this dissertation presents efficient resource allocation techniques that ensure tolerance against region-based faults, in distributed file storage networks and data center networks.
ContributorsBanerjee, Sujogya (Author) / Sen, Arunabha (Thesis advisor) / Xue, Guoliang (Committee member) / Richa, Andrea (Committee member) / Hurlbert, Glenn (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In this dissertation, remote plasma interactions with the surfaces of low-k interlayer dielectric (ILD), Cu and Cu adhesion layers are investigated. The first part of the study focuses on the simultaneous plasma treatment of ILD and chemical mechanical polishing (CMP) Cu surfaces using N2/H2 plasma processes. H atoms and radicals

In this dissertation, remote plasma interactions with the surfaces of low-k interlayer dielectric (ILD), Cu and Cu adhesion layers are investigated. The first part of the study focuses on the simultaneous plasma treatment of ILD and chemical mechanical polishing (CMP) Cu surfaces using N2/H2 plasma processes. H atoms and radicals in the plasma react with the carbon groups leading to carbon removal for the ILD films. Results indicate that an N2 plasma forms an amide-like layer on the surface which apparently leads to reduced carbon abstraction from an H2 plasma process. In addition, FTIR spectra indicate the formation of hydroxyl (Si-OH) groups following the plasma exposure. Increased temperature (380 °C) processing leads to a reduction of the hydroxyl group formation compared to ambient temperature processes, resulting in reduced changes of the dielectric constant. For CMP Cu surfaces, the carbonate contamination was removed by an H2 plasma process at elevated temperature while the C-C and C-H contamination was removed by an N2 plasma process at elevated temperature. The second part of this study examined oxide stability and cleaning of Ru surfaces as well as consequent Cu film thermal stability with the Ru layers. The ~2 monolayer native Ru oxide was reduced after H-plasma processing. The thermal stability or islanding of the Cu film on the Ru substrate was characterized by in-situ XPS. After plasma cleaning of the Ru adhesion layer, the deposited Cu exhibited full coverage. In contrast, for Cu deposition on the Ru native oxide substrate, Cu islanding was detected and was described in terms of grain boundary grooving and surface and interface energies. The thermal stability of 7 nm Ti, Pt and Ru ii interfacial adhesion layers between a Cu film (10 nm) and a Ta barrier layer (4 nm) have been investigated in the third part. The barrier properties and interfacial stability have been evaluated by Rutherford backscattering spectrometry (RBS). Atomic force microscopy (AFM) was used to measure the surfaces before and after annealing, and all the surfaces are relatively smooth excluding islanding or de-wetting phenomena as a cause of the instability. The RBS showed no discernible diffusion across the adhesion layer/Ta and Ta/Si interfaces which provides a stable underlying layer. For a Ti interfacial layer RBS indicates that during 400 °C annealing Ti interdiffuses through the Cu film and accumulates at the surface. For the Pt/Cu system Pt interdiffuion is detected which is less evident than Ti. Among the three adhesion layer candidates, Ru shows negligible diffusion into the Cu film indicating thermal stability at 400 °C.
ContributorsLiu, Xin (Author) / Nemanich, Robert (Thesis advisor) / Chamberlin, Ralph (Committee member) / Chen, Tingyong (Committee member) / Smith, David (Committee member) / Ponce, Fernando (Committee member) / Arizona State University (Publisher)
Created2012
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Description
We are expecting hundreds of cores per chip in the near future. However, scaling the memory architecture in manycore architectures becomes a major challenge. Cache coherence provides a single image of memory at any time in execution to all the cores, yet coherent cache architectures are believed will not scale

We are expecting hundreds of cores per chip in the near future. However, scaling the memory architecture in manycore architectures becomes a major challenge. Cache coherence provides a single image of memory at any time in execution to all the cores, yet coherent cache architectures are believed will not scale to hundreds and thousands of cores. In addition, caches and coherence logic already take 20-50% of the total power consumption of the processor and 30-60% of die area. Therefore, a more scalable architecture is needed for manycore architectures. Software Managed Manycore (SMM) architectures emerge as a solution. They have scalable memory design in which each core has direct access to only its local scratchpad memory, and any data transfers to/from other memories must be done explicitly in the application using Direct Memory Access (DMA) commands. Lack of automatic memory management in the hardware makes such architectures extremely power-efficient, but they also become difficult to program. If the code/data of the task mapped onto a core cannot fit in the local scratchpad memory, then DMA calls must be added to bring in the code/data before it is required, and it may need to be evicted after its use. However, doing this adds a lot of complexity to the programmer's job. Now programmers must worry about data management, on top of worrying about the functional correctness of the program - which is already quite complex. This dissertation presents a comprehensive compiler and runtime integration to automatically manage the code and data of each task in the limited local memory of the core. We firstly developed a Complete Circular Stack Management. It manages stack frames between the local memory and the main memory, and addresses the stack pointer problem as well. Though it works, we found we could further optimize the management for most cases. Thus a Smart Stack Data Management (SSDM) is provided. In this work, we formulate the stack data management problem and propose a greedy algorithm for the same. Later on, we propose a general cost estimation algorithm, based on which CMSM heuristic for code mapping problem is developed. Finally, heap data is dynamic in nature and therefore it is hard to manage it. We provide two schemes to manage unlimited amount of heap data in constant sized region in the local memory. In addition to those separate schemes for different kinds of data, we also provide a memory partition methodology.
ContributorsBai, Ke (Author) / Shrivastava, Aviral (Thesis advisor) / Chatha, Karamvir (Committee member) / Xue, Guoliang (Committee member) / Chakrabarti, Chaitali (Committee member) / Arizona State University (Publisher)
Created2014
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Description
In this dissertation, the interface chemistry and electronic structure of plasma-enhanced atomic layer deposited (PEALD) dielectrics on GaN are investigated with x-ray and ultraviolet photoemission spectroscopy (XPS and UPS). Three interrelated issues are discussed in this study: (1) PEALD dielectric growth process optimization, (2) interface electronic structure of comparative PEALD

In this dissertation, the interface chemistry and electronic structure of plasma-enhanced atomic layer deposited (PEALD) dielectrics on GaN are investigated with x-ray and ultraviolet photoemission spectroscopy (XPS and UPS). Three interrelated issues are discussed in this study: (1) PEALD dielectric growth process optimization, (2) interface electronic structure of comparative PEALD dielectrics on GaN, and (3) interface electronic structure of PEALD dielectrics on Ga- and N-face GaN. The first study involved an in-depth case study of PEALD Al2O3 growth using dimethylaluminum isopropoxide, with a special focus on oxygen plasma effects. Saturated and self-limiting growth of Al2O3 films were obtained with an enhanced growth rate within the PEALD temperature window (25-220 ºC). The properties of Al2O3 deposited at various temperatures were characterized to better understand the relation between the growth parameters and film properties. In the second study, the interface electronic structures of PEALD dielectrics on Ga-face GaN films were measured. Five promising dielectrics (Al2O3, HfO2, SiO2, La2O3, and ZnO) with a range of band gap energies were chosen. Prior to dielectric growth, a combined wet chemical and in-situ H2/N2 plasma clean process was employed to remove the carbon contamination and prepare the surface for dielectric deposition. The surface band bending and band offsets were measured by XPS and UPS for dielectrics on GaN. The trends of the experimental band offsets on GaN were related to the dielectric band gap energies. In addition, the experimental band offsets were near the calculated values based on the charge neutrality level model. The third study focused on the effect of the polarization bound charge of the Ga- and N-face GaN on interface electronic structures. A surface pretreatment process consisting of a NH4OH wet chemical and an in-situ NH3 plasma treatment was applied to remove carbon contamination, retain monolayer oxygen coverage, and potentially passivate N-vacancy related defects. The surface band bending and polarization charge compensation of Ga- and N-face GaN were investigated. The surface band bending and band offsets were determined for Al2O3, HfO2, and SiO2 on Ga- and N-face GaN. Different dielectric thicknesses and post deposition processing were investigated to understand process related defect formation and/or reduction.
ContributorsYang, Jialing (Author) / Nemanich, Robert J (Thesis advisor) / Chen, Tingyong (Committee member) / Peng, Xihong (Committee member) / Ponce, Fernando (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Vehicles powered by electricity and alternative-fuels are becoming a more popular form of transportation since they have less of an environmental impact than standard gasoline vehicles. Unfortunately, their success is currently inhibited by the sparseness of locations where the vehicles can refuel as well as the fact that many of

Vehicles powered by electricity and alternative-fuels are becoming a more popular form of transportation since they have less of an environmental impact than standard gasoline vehicles. Unfortunately, their success is currently inhibited by the sparseness of locations where the vehicles can refuel as well as the fact that many of the vehicles have a range that is less than those powered by gasoline. These factors together create a "range anxiety" in drivers, which causes the drivers to worry about the utility of alternative-fuel and electric vehicles and makes them less likely to purchase these vehicles. For the new vehicle technologies to thrive it is critical that range anxiety is minimized and performance is increased as much as possible through proper routing and scheduling. In the case of long distance trips taken by individual vehicles, the routes must be chosen such that the vehicles take the shortest routes while not running out of fuel on the trip. When many vehicles are to be routed during the day, if the refueling stations have limited capacity then care must be taken to avoid having too many vehicles arrive at the stations at any time. If the vehicles that will need to be routed in the future are unknown then this problem is stochastic. For fleets of vehicles serving scheduled operations, switching to alternative-fuels requires ensuring the schedules do not cause the vehicles to run out of fuel. This is especially problematic since the locations where the vehicles may refuel are limited due to the technology being new. This dissertation covers three related optimization problems: routing a single electric or alternative-fuel vehicle on a long distance trip, routing many electric vehicles in a network where the stations have limited capacity and the arrivals into the system are stochastic, and scheduling fleets of electric or alternative-fuel vehicles with limited locations to refuel. Different algorithms are proposed to solve each of the three problems, of which some are exact and some are heuristic. The algorithms are tested on both random data and data relating to the State of Arizona.
ContributorsAdler, Jonathan D (Author) / Mirchandani, Pitu B. (Thesis advisor) / Askin, Ronald (Committee member) / Gel, Esma (Committee member) / Xue, Guoliang (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2014